李源,蓝歆格,尹纯亚,商侨晏,王森,戚格瑞,葛祥一
LI Yuan,LAN Xinge,YIN Chunya,SHANG Qiaoyan,WANG Sen,QI Gerui,GE Xiangyi

• 1:国网浙江省电力有限公司龙游县供电公司
• 2:新疆大学电气工程学院

摘要(Abstract)：

为规范售电公司的市场行为，提升电力市场管理水平，需对售电公司开展信用评价。因此，基于Box-plot（箱形图）与正交化法，提出了一种改进的DHNN（离散型霍普菲尔德神经网络）信用评价模型。首先，分析梳理影响售电公司信用水平的因素，构建了包括基本信息、基础管理、合同管理、交易管理等11个指标在内的信用评价指标体系，并通过德尔菲法赋予指标权重。然后，对售电公司中指标异常数值进行处理，寻求其最优信用分值，实现对售电公司信用水平的客观评价。最后，通过算例验证所提模型的可行性，结果表明，该模型可对售电公司信用水平实现客观准确的评价。
To standardize the market conduct of electricity sales companies and elevate the power market management level, it is essential to conduct a credit evaluation of these companies. Therefore, based on Box-plot and orthogonalization methods, a credit evaluation model based on an enhanced discrete Hopfield neural network(DHNN) is proposed. Firstly, factors influencing the credit levels of electricity sales companies are analyzed, and a credit evaluation index system, which includes 11 indicators such as basic information, foundational management, contract management, and transaction management, is established. The weights for these indicators are determined using the Delphi method. Secondly, outliers in the indicators of electricity sales companies are addressed to derive optimal credit scores, enabling an objective assessment of their credit levels. Finally, the feasibility of the proposed model is verified through case studies. The results indicate that the model can objectively and accurately evaluate the credit levels of electricity sales companies.

关键词(KeyWords)： 售电公司;电力市场;信用评价;德尔菲法;箱形图;离散型霍普菲尔德神经网络
electricity sales company;electricity market;credit evaluation;Delphi method;Box-plot;DHNN

Abstract:

Keywords:

基金项目(Foundation): 新疆维吾尔自治区重点研发计划（2022B01016-3）;; 新疆维吾尔自治区青年科学基金（2022D01C85）

作者(Author): 李源,蓝歆格,尹纯亚,商侨晏,王森,戚格瑞,葛祥一
LI Yuan,LAN Xinge,YIN Chunya,SHANG Qiaoyan,WANG Sen,QI Gerui,GE Xiangyi

DOI: 10.19585/j.zjdl.202401009

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